基于蒙特卡洛模拟和动态事件树的储罐脆弱性评估

doi:10.16085/j.issn.1000-6613.2022-1376

摘要/Abstract

摘要：

泄漏事件是化工罐区多米诺事故的主要原因，随着泄漏时间增加，其后续的演化有多种可能的场景，而每种场景中受影响储罐的脆弱性变化也不同。为了更全面地分析泄漏事件发生后化工储罐的脆弱性，本文基于蒙特卡洛模拟和动态事件树提出了一种动态脆弱性评估方法。该方法考虑点火概率、协同效应等因素，利用Probit模型计算储罐失效概率，通过蒙特卡洛模拟得到火灾和爆炸事故场景下的动态脆弱性；利用动态事件树将每种事故场景发生概率及对应的脆弱性变化按照时间序列结合，从而比较全面地描述泄漏事件的后续演化场景，得到考虑火灾和爆炸场景的总体脆弱性。使用两个案例验证说明了该方法的可行性，结果表明该方法能实现动态的预测和评估化工储罐的脆弱性。

关键词: 多米诺效应, 蒙特卡洛模拟, 动态建模, 储罐脆弱性, 预测评估

Abstract:

The leakage event is the main cause of domino accident in chemical tank farm. With the increase of leakage time, there are many possible scenarios for its subsequent evolution, and the vulnerability of affected tanks in each scenario is also different. In order to comprehensively analyze the vulnerability of chemical storage tanks after leakage event, a dynamic vulnerability assessment method based on Monte Carlo simulation and dynamic event tree was proposed in this paper. In this method, the ignition probability, synergistic effect and other factors were considered, and the failure probability of storage tanks was calculated by Probit model. The dynamic vulnerability under fire and explosion accident scenarios was obtained by Monte Carlo simulation. The dynamic event tree was used to combine the occurrence probability of each accident scenario and the corresponding vulnerability change according to the time series, so as to comprehensively describe the subsequent evolution scenario of the leakage event, and obtain the total vulnerability of the fire and explosion scenarios. The feasibility of this method was verified by two cases. The results showed that this method could dynamically predict and assess the vulnerability of chemical storage tanks.

Key words: domino effects, Monte Carlo simulation, dynamic modeling, tank vulnerability, prediction and evaluatio

中图分类号:

X937

赵景斌, 王彦富, 王涛, 马伟恺, 王琛. 基于蒙特卡洛模拟和动态事件树的储罐脆弱性评估[J]. 化工进展, 2023, 42(5): 2751-2759.

ZHAO Jingbin, WANG Yanfu, WANG Tao, MA Weikai, WANG Chen. Vulnerability assessment of storage tanks based on Monte Carlo simulation and dynamic event tree[J]. Chemical Industry and Engineering Progress, 2023, 42(5): 2751-2759.

图/表 13

图1 基于蒙特卡洛模拟和动态事件树的脆弱性分析流程

图2 易燃液体泄漏事件树

表1 参数a,b,c,d的取值

储罐	a	b	c	d
常压储罐	-18.96	2.44	-1.13	-2.67×10^-5V+9.9
压力储罐	-42.44	4.33	-0.95	8.85V^0.032

图3 泄漏事件的动态事件树分析（图中FF表示闪火，CA表示具备发生爆炸的条件）

图4 储罐布局与物理效应（图中数据前者为热辐射值，单位为kW/m2；后者为爆炸超压值，单位为kPa）

图5 T2、T3的动态脆弱性

图6 罐区平面示意图

表2 各储罐相关参数

储罐	储存物质	直径/m	高度/m	额定容积/m³	实际储量/m³
T1	苯	17	13	2700	2000
T2	苯	17	13	2700	800
T3	苯	17	13	2700	1400
T4	苯	17	13	2700	1200
T5	甲醇	17	13	2700	600
T6	甲醇	17	13	2700	1500

表3 T i 接收T j 的热辐射值 (kW/m2)

T _j	T _i
T _j	T1	T2	T3	T4	T5	T6
T1	—	35	7	23	14.7	5
T2	16	—	35	8.6	23	14.7
T3	3.8	16	—	3.1	8.6	23
T4	23	14.6	5	—	35	7
T5	4.5	20.8	9.4	11	—	29
T6	1.2	4.5	20.8	1.5	11	—

图7 火灾事故动态脆弱性

表4 可燃物质量与爆炸当量梯度表

情景	M_f/kg	M_TNT/kg
1	50	25.1
2	200	100.4
3	400	200.9
4	800	401.7
5	1500	753.2
6	3000	1506.4
7	6000	3012.9
8	10000	5021.4

图8 8种情景下的爆炸事故动态脆弱性（图中S1~S8分别对应表4中的8种情景）

图9 考虑火灾和爆炸情景的总体脆弱性

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